Practical energy-efficient reverse osmosis: experimental and modeling investigation for high-temperature water treatment
Bibliographic record
Abstract
Reducing the energy demands of conventional water treatment systems is crucial. High-temperature treatment can be efficient when waste heat is freely available, such as from geothermal or steam-assisted gravity drainage (SAGD) produced water. These industrial streams present both an opportunity and a challenge: elevated temperatures enable integration with heat-recovery systems, yet most commercial membranes lose performance or stability under such conditions. In this study, we developed and evaluated lab-synthesized thin-film composite (TFC) high-temperature reverse osmosis (HTRO) membranes capable of stable operation from room temperature to 120 °C. The best-performing membrane (TFC3, made with 2 wt% TAP) achieved 255 LMH flux at 120 °C, over 190 % higher than the control membrane, and maintained >96 % salt rejection with only 12.9 % flux decline over seven hours of continuous operation. These results show higher permeability and thermal stability than the commercial AG membrane, due to greater polyamide crosslinking and better substrate thermal resistance. A temperature-dependent modeling framework was developed and validated against experimental data. Both convective and diffusive transport models were evaluated, with the diffusive model showing better agreement with the experiments. Energy analysis showed that optimized HTRO membranes can significantly reduce specific energy consumption (SEC) at high temperatures relative to ambient-temperature RO, reaching values as low as ~0.5 kWh/m 3 under geothermal-like conditions. These findings highlight the potential of high-performance HTRO membranes to address the energy intensity of conventional water treatment in thermally intensive industries. • Lab-made HTRO TFC membranes show stable operation from 25 to 120 °C in extended testing. • Trifunctional monomer boosts crosslinking, permeability, and stability in high-T TFCs • Diffusive-flow model best matches temperature-dependent flux and salt transport data. • Operating on hot feeds reduces SEC vs ambient RO; SAGD and geothermal cases assessed. • HTRO–ORC integration recovers energy while producing freshwater efficiently at scale.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".